code: def __new__(cls, name, bases, attr):
      if "train_one_batch" in attr:
          attr["train_one_batch"] = ModelMeta.buffer_operation(
              attr["train_one_batch"]
          )
  
      return super(ModelMeta, cls).__new__(cls, name, bases, attr)
  
imports: import os
  import gc
  import time
  import json
  import zipfile
  import numpy
  from functools import wraps
  from collections import Iterable
  from singa import tensor
  from singa import autograd
  from singa import layer
  from .tensor import Tensor
  from .None import singa_wrap
label_desc: Use image node_id 2 for calling the ModelMeta obj's underlying member method code with example usage: obj.__new__(cls, name, bases, attr) and returns: super